A human-made statistical method for determining the sample size required to detect a specified effect size with a given statistical power (typically 0.80) at a predetermined significance level (typically α=0.05). Its parameters are: (1) the anticipated effect size, (2) the desired statistical power (1−β), (3) the significance level (α), and (4) the test type (one-tailed or two-tailed). It persists through mathematical formulation in probability theory and adoption as a standard requirement in research protocol design and peer review. [formal: potentia analysis | substrate: mind | horizon: a life | explicit: yes | epoch: 0.01]
Accepted ontology entry
power-analysis
A human-made statistical method for determining the sample size required to detect a specified effect size with a given statistical power (typically 0.80) at a predetermined significance level (typically α=0.05). Its parameters are: (1) th…
Definition
Why it is in scope
A human-made statistical method for determining the sample size needed to detect a specified effect with a given probability, built to persist through mathematical formulation and research protocol standards
Names and aliases
- power-analysisen · CANONICAL
Relations from this entry
- cmrw5yq7p001qkyo6dio7rpdtDEPENDS_ON →
Removal test: remove effect-size and power-analysis cannot compute — power analysis requires specifying the expected effect size as a core parameter. Without effect-size, the method has no operational mechanism.
- cmrxj3acr03cmsoacx73fal1oDEPENDS_ON →
Remove statistics and power-analysis stops operating: power analysis uses statistical distributions (normal, t, F), effect sizes, alpha/beta error rates, and computational statistical methods. Without statistical theory, power analysis has no framework, no calculations, and no operational meaning. which-came-first: statistics (epoch 0.12) predates power-analysis (epoch 0.15).
- cmrvpfry601wq2ceichuy36vpSERVES →
Power analysis is designed and maintained for the sake of experimental design: its primary purpose is to determine sample sizes and detect effects within experimental frameworks. The test is 'for whose sake?' — power analysis exists to serve experimental design.
- cmrxj3acr03cmsoacx73fal1oINSTANCE_OF →
Power analysis IS a specific kind of statistics — a statistical technique for determining sample size and detecting effects. A competent speaker would say 'power analysis is a kind of statistical method/technique.' The nearest kind is statistics itself (no intermediate category between power analysis and statistics).
Relations to this entry
No accepted relations in this direction.
Record identity
- Created
- Jul 22, 2026, 2:20 PM UTC
- Content hash
- c471d76d59eea6cf5b19c3a26498c0d8b437784cdaadfe05ea0dcfc5d0ac36af